Deriving Group A Streptococcus Typing Information from Short-Read Whole-Genome Sequencing Data

Athey, Taryn; Teatero, Sarah; Li, Aimin; Marchand-Austin, Alex; Beall, Bernard; Fittipaldi, Nahuel

doi:10.1128/jcm.00029-14

Cited by 38 publications

(56 citation statements)

References 33 publications

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“…The FASTQ files for the isolates described in Athey et al (2014) ( n = 191) were obtained from the European Nucleotide Archive (ENA) study PRJNA233611.…”

Section: Methodsmentioning

confidence: 99%

Whole genome sequencing of group AStreptococcus: development and evaluation of an automated pipeline foremmgene typing

Kapatai

Coelho

Platt

et al. 2017

PeerJ

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Streptococcus pyogenes group A Streptococcus (GAS) is the most common cause of bacterial throat infections, and can cause mild to severe skin and soft tissue infections, including impetigo, erysipelas, necrotizing fasciitis, as well as systemic and fatal infections including septicaemia and meningitis. Estimated annual incidence for invasive group A streptococcal infection (iGAS) in industrialised countries is approximately three per 100,000 per year. Typing is currently used in England and Wales to monitor bacterial strains of S. pyogenes causing invasive infections and those isolated from patients and healthcare/care workers in cluster and outbreak situations. Sequence analysis of the emm gene is the currently accepted gold standard methodology for GAS typing. A comprehensive database of emm types observed from superficial and invasive GAS strains from England and Wales informs outbreak control teams during investigations. Each year the Bacterial Reference Department, Public Health England (PHE) receives approximately 3,000 GAS isolates from England and Wales. In April 2014 the Bacterial Reference Department, PHE began genomic sequencing of referred S. pyogenes isolates and those pertaining to selected elderly/nursing care or maternity clusters from 2010 to inform future reference services and outbreak analysis (n = 3,047). In line with the modernizing strategy of PHE, we developed a novel bioinformatics pipeline that can predict emm types using whole genome sequence (WGS) data. The efficiency of this method was measured by comparing the emm type assigned by this method against the result from the current gold standard methodology; concordance to emm subtype level was observed in 93.8% (2,852/3,040) of our cases, whereas in 2.4% (n = 72) of our cases concordance was observed to emm type level. The remaining 3.8% (n = 117) of our cases corresponded to novel types/subtypes, contamination, laboratory sample transcription errors or problems arising from high sequence similarity of the allele sequence or low mapping coverage. De novo assembly analysis was performed in the two latter groups (n = 72 + 117) and was able to diagnose the problem and where possible resolve the discordance (60/72 and 20/117, respectively). Overall, we have demonstrated that our WGS emm-typing pipeline is a reliable and robust system that can be implemented to determine emm type for the routine service.

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“…The FASTQ files for the isolates described in Athey et al (2014) ( n = 191) were obtained from the European Nucleotide Archive (ENA) study PRJNA233611.…”

Section: Methodsmentioning

confidence: 99%

Whole genome sequencing of group AStreptococcus: development and evaluation of an automated pipeline foremmgene typing

Kapatai

Coelho

Platt

et al. 2017

PeerJ

View full text Add to dashboard Cite

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“…The number and quality of sequence reads for each FASTQ file were confirmed using FastQC (Babraham Bioscience Technologies, Cambridge, United Kingdom). The emm types were identified using emm_pipeline.pl (14). Polymorphisms were identified first using VAAL (15) and later using Musket, Novoalign, and Freebayes (15).…”

Section: Methodsmentioning

confidence: 99%

Clinical Laboratory Response to a Mock Outbreak of Invasive Bacterial Infections: a Preparedness Study

et al. 2014

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Large hospital-based clinical laboratories must be prepared to rapidly investigate potential infectious disease outbreaks. To challenge the ability of our molecular diagnostics laboratory to use whole-genome sequencing in a potential outbreak scenario and identify impediments to these efforts, we studied 84 invasive serotype emm59 group A streptococcus (GAS) strains collected in the United States. We performed a rapid-response exercise to the mock outbreak scenario using whole-genome sequencing, genome-wide transcript analysis, and mouse virulence studies. The protocol changes installed in response to the lessons learned were tested in a second iteration. The initial investigation was completed in 9 days. Whole-genome sequencing showed that the invasive infections were caused by multiple subclones of epidemic emm59 GAS strains likely spread to the United States from Canada. The phylogenetic tree showed a strong temporal-spatial structure with diversity in mobile genetic element content, features that are useful for identifying closely related strains and possible transmission events. The genome data informed the epidemiology, identifying multiple patients who likely acquired the organisms through direct person-to-person transmission. Transcriptome analysis unexpectedly revealed significantly altered expression of genes encoding a two-component regulator and the hyaluronic acid capsule virulence factor. Mouse infection studies confirmed a high-virulence capacity of these emm59 organisms. Whole-genome sequencing, coupled with transcriptome analysis and animal virulence studies, can be rapidly performed in a clinical environment to effectively contribute to patient care decisions and public health maneuvers.

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“…Classical serologic M typing in many laboratories has been replaced by emm typing, which in almost all cases predicts the classical M serotype (10,11). To date, Ͼ200 different emm types have been reported.…”

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confidence: 99%

Epidemiology of Invasive Group A Streptococcal Disease in Alaska, 2001 to 2013

et al. 2016

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The Arctic Investigations Program (AIP) began surveillance for invasive group A streptococcal (GAS) infections in Alaska in 2000 as part of the invasive bacterial diseases population-based laboratory surveillance program. Between 2001 and 2013, there were 516 cases of GAS infection reported, for an overall annual incidence of 5.8 cases per 100,000 persons with 56 deaths (case fatality rate, 10.7%). Of the 516 confirmed cases of invasive GAS infection, 422 (82%) had isolates available for laboratory analysis. All isolates were susceptible to penicillin, cefotaxime, and levofloxacin. Resistance to tetracycline, erythromycin, and clindamycin was seen in 11% (n ‫؍‬ 8), 5.8% (n ‫؍‬ 20), and 1.2% (n ‫؍‬ 4) of the isolates, respectively. A total of 51 emm types were identified, of which emm1 (11.1%) was the most prevalent, followed by emm82 (8.8%), emm49 (7.8%), emm12 and emm3 (6.6% each), emm89 (6.2%), emm108 (5.5%), emm28 (4.7%), emm92 (4%), and emm41 (3.8%). The five most common emm types accounted for 41% of isolates. The emm types in the proposed 26-valent and 30-valent vaccines accounted for 56% and 78% of all cases, respectively. GAS remains an important cause of invasive bacterial disease in Alaska. Continued surveillance of GAS infections will help improve understanding of the epidemiology of invasive disease, with an impact on disease control, notification of outbreaks, and vaccine development.

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Deriving Group A Streptococcus Typing Information from Short-Read Whole-Genome Sequencing Data

Cited by 38 publications

References 33 publications

Whole genome sequencing of group AStreptococcus: development and evaluation of an automated pipeline foremmgene typing

Whole genome sequencing of group AStreptococcus: development and evaluation of an automated pipeline foremmgene typing

Clinical Laboratory Response to a Mock Outbreak of Invasive Bacterial Infections: a Preparedness Study

Epidemiology of Invasive Group A Streptococcal Disease in Alaska, 2001 to 2013

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